In the first study, I have 2 populations (equal numbers) of Nurses (n=155); patients (N=155). However, I have 2 different data sets snd different surveys, whereby for the nurses we looked at nurses' performance-related alarm fatigue and for the patients, we looked at their satisfaction with nurses' care. We would like to look at the correlation between nurses' performance-related alarm fatigue and patients' satisfaction.
@Aladeen Alloubani, as I superficially understand, variabe is not highly correlated to correlate different variable with different data sets. Like for example is the formative type of variables (for example correlating a set of symptoms in a particular disease). Variables that are highly correlated are those reflective type (for example is correlating a disease to its identified list of symptoms). In your study, it would be nice if you would correlate nurse performance alarm related fatigue to nurse compassion. It means that a variable is highly correlated within same variable and same data sets. ✌
Are both population ‘normal?’ Do you understand the nature of Normality in quantitative research - look it up. If they are both normal populations then one could assume that these correlations could be undertaken. However what about the two surveys you are using? Are they validated instruments in themselves? To me it makes more sense to correlate nurses fatigue alarm ( definition for this?) with nurses lack of compassion in the one data set - you are wanting a correlation between this material not between different surveys and data sets.
Open this... https://towardsdatascience.com/linear-regression-detailed-view-ea73175f6e86
Good Luck
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